We present an innovative method based on the application of inverse yield models for producing spatially explicit estimations of forest age. Firstly, a raster growing stock volume map was produced using the non-parametric kNearest Neighbors estimation method on the basis of IRS LISS-III remotely sen sed imagery and field data collected in the framework of a local forest inventory. Secondly, species-specific inverted yield equations were applied to estimate forest age as a function of growing stock volume. The method was tested in 128 000 ha of even-aged forests in central Italy (Molise region). The accuracy of the method was assessed using an independent dataset of 305 units from a local standwise forest inventory. The results demonstrated that the fo rest age map was accurate, with a root mean square error of 15.8 years (30% of the mean of field values), and useful for supporting forest management purposes, such as the assessment of harvesting potential and ecosystem services. Thanks to the use of remotely sensed data and spatial modeling, the proposed approach is cost-effective and easily replicable for vast regions.

Spatially explicit estimation of forest age by integrating remotely sensed data and inverse yield modeling techniques / Frate, L.; Carranza, M. L.; Garfì, V.; Di Febbraro, M.; Tonti, D.; Marchetti, M.; Ottaviano, M.; Santopuoli, G.; Chirici, G.. - In: IFOREST. - ISSN 1971-7458. - 9:Feb 2016(2016), pp. 63-71. [10.3832/ifor1529-008]

Spatially explicit estimation of forest age by integrating remotely sensed data and inverse yield modeling techniques

Marchetti, M.;
2016

Abstract

We present an innovative method based on the application of inverse yield models for producing spatially explicit estimations of forest age. Firstly, a raster growing stock volume map was produced using the non-parametric kNearest Neighbors estimation method on the basis of IRS LISS-III remotely sen sed imagery and field data collected in the framework of a local forest inventory. Secondly, species-specific inverted yield equations were applied to estimate forest age as a function of growing stock volume. The method was tested in 128 000 ha of even-aged forests in central Italy (Molise region). The accuracy of the method was assessed using an independent dataset of 305 units from a local standwise forest inventory. The results demonstrated that the fo rest age map was accurate, with a root mean square error of 15.8 years (30% of the mean of field values), and useful for supporting forest management purposes, such as the assessment of harvesting potential and ecosystem services. Thanks to the use of remotely sensed data and spatial modeling, the proposed approach is cost-effective and easily replicable for vast regions.
2016
Forest inventory; Growing stock; IRS LISS-III; K-Nearest neighbors; Mapping; Forestry; Ecology; Nature and Landscape Conservation
01 Pubblicazione su rivista::01a Articolo in rivista
Spatially explicit estimation of forest age by integrating remotely sensed data and inverse yield modeling techniques / Frate, L.; Carranza, M. L.; Garfì, V.; Di Febbraro, M.; Tonti, D.; Marchetti, M.; Ottaviano, M.; Santopuoli, G.; Chirici, G.. - In: IFOREST. - ISSN 1971-7458. - 9:Feb 2016(2016), pp. 63-71. [10.3832/ifor1529-008]
File allegati a questo prodotto
Non ci sono file associati a questo prodotto.

I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.

Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11573/1715375
 Attenzione

Attenzione! I dati visualizzati non sono stati sottoposti a validazione da parte dell'ateneo

Citazioni
  • ???jsp.display-item.citation.pmc??? ND
  • Scopus 16
  • ???jsp.display-item.citation.isi??? 16
social impact